2004 | OriginalPaper | Buchkapitel
Dynamic Adjustment of Sliding Windows over Data Streams
verfasst von : Dongdong Zhang, Jianzhong Li, Zhaogong Zhang, Weiping Wang, Longjiang Guo
Erschienen in: Advances in Web-Age Information Management
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
The data stream systems provide sliding windows to preserve the arrival of recent streaming data in order to support continuous queries in real-time. In this paper, we consider the problem of adjusting the buffer size of sliding windows dynamically when the rate of streaming data changes or when queries start or end. Based on the status of available memory resource and the requirement of queries for memory, we propose the corresponding algorithms of adjustment with greedy method and dynamic programming method, which minimize the total error of queries or achieve low memory overhead. The analytical and experimental results show that our algorithms can be applied to the data stream systems efficiently.